As the volume of content available on the Internet continues to grow exponentially, the importance of Internet search engines and search technology is reinforced. Virtually every Internet user uses one or more search engines such as Google, Yahoo or the like to locate relevant Internet content of interest to them on a more or less frequent basis. With the large quantity of material available on the Internet, various tools and methods for the refinement of search engine results have been created and tested with varying degrees of success.
The most popular search engines available on the Internet, including Google, are primarily based upon the user entering a set of text search terms through a search engine interface and those text search terms are used to extract a result set from the index created or administered by the search engine. One of the limitations however to a purely text-based search is that if you use a text search term which can have more than one definition or meaning, the result set which is retrieved will not be as focused or relevant to the topic of interest as might be desired.
Search engines have endeavored in the past to internally assemble by use of proprietary algorithms or the like ranked indexes of content to inquisitively try to provide more relevant results to the user, or in more likely circumstances to at the very least provide the ability for the search engines to sell higher ranked positions in their index to generate advertising revenue.
To date one of the primary methods by which a provider of search services is able to provide focus or limitation in the results sets to be returned in response to basic text queries such as this is to limit the content within the index—for example, if a particular search provider is interested only in providing medical publication results, then they need to create an index which contains pointers and information relating to medical publication content. In this way, the results returned from a search exercised upon their text index will be limited similarly to the medical publication content contained therein. It would be desirable to be able to provide a method of ranking or limiting search results in a more general text index without the need to physically restrict the types of content which were indexed therein.
Another limitation of purely text-based searching is the search engine provided with a single text search term is not able to provide search results which encompass more than one different word or term having the same definition. In circumstances where different locales or dialects use different words to describe the same thing, it would be necessary to include both or all of those text search terms in the search query fed to the search engine in order to ensure that results were returned from the application of that search query to the index covering the use of all of the different terms sharing the same definition. If there were a way to associate a particular text search term with other similar terms by linking it through its definition this could allow for enhancements in search technology.
All of these various limitations to present-day text-based search engines and search techniques on the Internet are related or traceable in some way to the fact that a text-based search does not itself incorporated into the search criteria or the characterization or prioritization of the search results any one or more actual “definitions” of each of the text search terms which are included in the search query fed to the search engine and applied to the indexing question. By re-orienting or adding to the criteria used in the application of a search query to a particular search engine or index the actual semantics or definitions of those terms, the relevance of the search results can be enhanced. As well, the development of such as searching methodology will allow for the aggregation as it is used by various search users of a semantically associated index of Web content which beyond being indexed in a way that keeps track of various pieces of content solely by the presence of a particular text term therein will over time aggregate the necessary information to understand in the case of terms which might have more than one definition, only one of which might be relevant to the content in that item, what is the proper definition or relevance of the terms present therein and/or whether or not that particular piece of Internet content is actually semantically relevant to the query being submitted and processed. Beyond its use as an enhanced searching tool this type of an Internet text index would have other commercial uses including the ability to provide enhanced relevance in the serving of content such as advertising.
Beyond pure text correlation, one of the primary ways that a user right now can endeavor to narrow down a text search to isolate contents of the definitional nature they desire is to provide multiple text search terms with the proper query operators associating them and by this way endeavor to narrow down the results returned in the execution of a query against the text index [for example if you were looking for references related to apples as fruit, you could execute a query that searched for the terms APPLE and FRUIT, with a view to isolating or minimizing the references that you received in your query result set from a large number of those pertaining to for example, the Apple Computer Company.] Provision of a text indexing tool which will allow for semantic refinement or limitation of the search results would be desirable and effective over what is being done currently in basic text searching.